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library(tidyverse)

data_to_viz <- read_csv("data/data-to-explore.csv")

data_to_viz  %>% 
  select(subject, 
         enrollment_reason) %>%
mutate(subject = recode(subject, 
                        "AnPhA" = "Anatomy",
                        "BioA" = "Biology", 
                        "FrScA" = "Forensics", 
                        "OcnA" =  "Oceanography", 
                        "PhysA" = "Physics")) %>%
ggplot() +
     geom_bar(mapping = aes(x = enrollment_reason, fill = enrollment_reason)) +
     labs(title = "Enrollment Reason by Subject",
                   caption = "Why Did Students Choose to Enroll in the Course?", 
                   y = "Enrollment Reason", fill = "Enrollment Reason") +
          facet_wrap(~subject) +
          theme_minimal() + 
          theme(axis.title.x=element_blank(),
                axis.text.x=element_blank())

The faceted bar graph shown above answers our research question, “Why did students chose to enroll in a particular course?” Each bar graph indicates the number of students who chose to enroll in a given course (of the five offered) for each of the six reasons shown in the legend. For three subjects (Anatomy, Oceanography, and Forensics), students primarily chose to enroll in the online course because it was not offered at their local school. For Biology and Physics, the primary reason for enrollment was an unspecified “Other” reason. Only Physics had students enroll for course recovery, which could alert professors to pay particular attention to these students’ progress in the course early in the semester. Furthermore, Forensics had the highest volume of students who chose to take the course online because of a lack of availability at their local schools. This suggests that there is a high interest in Forensics as a subject but low availability for many students. Various hypotheses could be formed as to how this will affect student performance (perhaps choosing to look for a course at a location other than their local school will correspond to increased motivation), but this particular graph does not explore these. Further analysis is necessary to explore the implications of the data shown.